最新的UiPath Certified Professional Specialized AI Professional v1.0 - UiPath-SAIv1免費考試真題

A. Improves the extractor accuracy by learning from the classification result.

B. Allows the extractor to improve its prediction over time by using better OCR (Optical Character Recognition) engines.

C. Allows a human to validate and correct the extracted data.

D. Allows the model to learn from human-validated data.

A. When setting up a stream.

B. In the validation page.

C. In Admin > Models.

D. On the models tab.

A. The model's confidence that a specific concept exists within a communication.

B. The difference between label suggestions and label predictions in a training process.

C. The understanding of the parent-label relationship when assigning label predictions.

D. The identification of a specific span of text as a value for a particular entity type.

A. ApplyOcrOnPdf -> No DegreeOfParallelism -> -1 DetectCheckboxes -> False

B. ApplyOcrOnPdf -> No DegreeOfParallelism -> True DetectCheckboxes -> True

C. ApplyOcrOnPdf -> Auto DegreeOfParallelism -> Max DetectCheckboxes -> True

D. ApplyOcrOnPdf -> Auto

E. ApplyOcrOnPdf -> Auto DegreeOfParallelism -> -1 DetectCheckboxes -> True

A. To create and edit a Taxonomy file specific to the current automation project.

B. To present a document processing specific user interface for validating and correcting automatic classification outputs.

C. To select the type of ML that can be used in the project.

D. To select which extractors are trained for each document type and field.

A. Name and labels.

B. Name and description.

C. Name, description, and labels.

D. Name, description, and permissions.

A. A solution for combining different approaches to extract information from workflows.

B. A solution for combining different approaches to extract entities from Word documents such as contracts and agreements.

C. A solution that offers the ability to digitize, extract, validate, and train data from documents.

D. A solution for the processing of Excel files for extracting data tables.

A. Load Taxonomy, Digitization, Classification, Data Extraction, and Data Validation Export

B. Import, Classification, Text Extractor, and Data Validation

C. Load Taxonomy, Digitization, Categorization, Data Validation, and Export

D. Load Document, Categorization, Data Extraction, and Validation

A. IntelligentOCR is simply a rebranding of the OCR (Optical Character Recognition), both of them being methods that read text from images, recognizing each character and its position.

B. OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position, while IntelligentOCR is an enhanced version of it that can also work with noisier input data.

C. IntelligentOCR is a UiPath Studio activity package that contains all the activities needed to enable information extraction, while OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position.

D. OCR (Optical Character Recognition) is a UiPath Studio activity package that contains IntelligentOCR as an activity used to read text from images, recognizing each character and its position. OCR is widely used in Document Understanding processes.

A. To eliminate the need for exception handling in workflows.

B. To create custom workflows from scratch.

C. To offer a fully functional document processing tool that is easy to use and execute.

D. To integrate with other connected automations seamlessly.

A. On a VM, Orchestrator Bucket, and Network Attached Storage.

B. Orchestrator Bucket and Queue Item.

C. Locally, Temp Folder, Network Attached Storage, and Orchestrator Bucket.

D. Network Attached Storage and Orchestrator Bucket.